Method and arrangement for interferance attenuation

ABSTRACT

A method of attenuating interference in a wideband telecommunications system comprises setting an interference level threshold; sampling the received signal; storing the sample values as first sample value vectors of a  5  predetermined length, forming prediction matrices of the first sample value vectors; modifying prediction matrices in such a way that the interference components and the components of the desired signal are separated from each other; forming signal matrices by performing rank reduction for each prediction matrix by rejecting those sample values or elements representing  10  them that exceed the interference level threshold; forming second sample value vectors of the signal matrices, the second sample value vectors being at least substantially of the same length as the first sample value vectors; summing up sample values of second sample value vectors time-coherently to average the noise by sliding the sample value window, the length of which is  15  determined preferably by the length of the first sample value vectors.

FIELD OF THE INVENTION

[0001] The invention relates to a method and an arrangement forinterference attenuation in a wideband telecommunications system.

BACKGROUND OF THE INVENTION

[0002] On the radio path, both AWGN, i.e. additive white gaussian noise,and different interference signals or fading multipath-propagated signalcomponents of different signals are summed up in the desired signal.Interferences are usually caused inadvertently by other systems or otherusers of the same system, but they can also be caused deliberately.There have been attempts to eliminate or attenuate interferences withfor instance different coding-decoding methods, channel equalizers andfiltering. However, it has been problematic to find a sufficientlyefficient noise-attenuation method that would be applicable to widebandtelecommunications systems. The problem has specifically been to findsuch a method that would efficiently attenuate also relatively widebandinterference in wideband data transmission systems.

[0003] Singular value decomposition, i.e. SVD, refers to numeric signalprocessing applied to several objects of use, such as spectral analysis,design of filters, and reduction and estimation of model orders.Singular value decomposition can be applied directly to processing datamatrices, and it is applicable to both real and complex value matrices.Singular value decomposition is described in more detail in publicationby Todd K. Moon, Wynn C. Stirling: Mathematical Methods and Algorithmsfor Signal Processing, Prentice Hall, 2000, which is incorporated asreference herein.

BRIEF DESCRIPTION OF THE INVENTION

[0004] An object of the invention is to implement an improved method ofattenuating particularly such interference that is not previously known.This is achieved with a method of attenuating interference in a widebandtelecommunications system. The method comprises setting an interferencelevel threshold; sampling the received signal; storing the sample valuesas first sample value vectors of a predetermined length, formingprediction matrices of the first sample value vectors; modifyingprediction matrices in such a way that the interference components andthe components of the desired signal are separated from each other;forming signal matrices by performing rank reduction for each predictionmatrix by rejecting those sample values or elements representing themthat exceed the interference level threshold; forming second samplevalue vectors of the signal matrices, the second sample value vectorsbeing at least substantially of the same length as the first samplevalue vectors; summing up sample values of second sample value vectorstime-coherently to average the noise by sliding the sample value window,the length of which is determined preferably by the length of the firstsample value vectors.

[0005] Further, an object of the invention is a receiver in a widebandtelecommunications system, implementing the method, interference beingattenuated in the receiver. The receiver comprises means for setting aninterference level threshold; the receiver comprises means for samplingthe received signal; the receiver comprises means for storing the samplevalues as first sample value vectors of a predetermined length; thereceiver comprises means for forming prediction matrices of the firstsample value vectors; the receiver comprises means for modifyingprediction matrices in such a way that the interference components andthe components of the desired signal are separated from each other; thereceiver comprises means for forming signal matrices by performing rankreduction for each modified prediction matrix by rejecting those samplevalues or elements representing them that exceed the interference levelthreshold; the receiver comprises means for forming second sample valuevectors of the signal matrices, the second sample value vectors being atleast substantially of the same length as the first sample valuevectors; the receiver comprises means for summing up sample values ofsecond sample value vectors time-coherently to average the noise bysliding the sample value window, the length of which is determinedpreferably by the length of the first sample value vectors.

[0006] Preferred embodiments of the invention are disclosed in thedependent claims.

[0007] The invention is based on the idea that the sample values takenfrom the received signal are stored as vectors of a desired length, ofwhich data matrices are formed, being called prediction matrices. Theprediction matrices are modified in such a way that the interferencecomponents and the components of the desired signal are separated fromeach other. This can be implemented for example by factorizing thematrix by means of singular value decomposition. Next, those samplevalues, elements representing the sample values or, in the case ofsignal value decomposition, singular values and corresponding singularvectors that exceed the set interference level threshold are rejected.In this way, rank reduction is preferably performed for the matrix inaccordance with the Eckhart-Young theorem. Next, new sample valuevectors are formed using the remaining values. In this way, interferencesummed up in the signal in the channel can be attenuated. Finally, noiseis averaged by adding up sample values in a time-coherent manner.

[0008] A plurality of advantages is achieved with the method and systemaccording to the invention. Interference in a receiver of a widebandsystem can be efficiently attenuated with the method of the invention.Relatively wideband interference not known in advance can also beremoved by means of the method of the invention by determining a slidingsample value window to be of an appropriate size relative to theinterfering system: with a narrow sample value window, the momentaryrelative bandwidth of the interference can be made narrow compared withthe bandwidth of the desired signal.

BRIEF DESCRIPTION OF THE FIGURES

[0009] The invention will now be described in greater detail inconnection with preferred embodiments, with reference to the attacheddrawings, in which

[0010]FIG. 1 shows an example of a telecommunications system;

[0011]FIG. 2 shows a second example of a telecommunications system;

[0012]FIG. 3 shows a flow chart of the method steps for attenuatinginterference in a wideband telecommunications system;

[0013]FIG. 4 illustrates an example of rank reduction in the matrix;

[0014]FIG. 5 illustrates an example of averaging noise;

[0015]FIG. 6 shows an example of a receiver;

[0016]FIG. 7 shows an example of a simulation result.

DESCRIPTION OF EMBODIMENTS

[0017] The solution according to the invention is particularlyapplicable to the MC-CDMA (Multi Carrier Code Division Multiple Access)radio system utilizing direct sequence (DS) technique. Other objects ofapplication can include satellite systems, military telecommunicationssystems and private non-cellular networks. The solution according to theinvention is not confined to these, however.

[0018] The following example illustrates preferred embodiments of theinvention in the UMTS (Universal Mobile Telephone System) without,however, restricting the invention thereto.

[0019] The structure of a mobile system is described with reference toFIG. 1. The main parts of the mobile system are a core network CN, aUMTS terrestrial radio access network UTRAN and user equipment Ue. Theinterface between the CN and the UTRAN is called Iu, the interfacebetween the UTRAN and the Ue being called Uu.

[0020] UTRAN is formed of radio network subsystems RNS. The interfacebetween the RNSs is called Iur. The RNS is formed of a radio networkcontroller RNC and of one or more nodes B. The interface between the RNCand B is called Iub. The coverage area of the node B, i.e. the cell, isdenoted by C in the figure.

[0021] The description shown in FIG. 1 is at rather a general level sothat FIG. 2 shows a more detailed example of a cellular radio network.FIG. 2 contains only the most essential blocks, but it will be obviousto a person skilled in the art that a conventional cellular radionetwork also includes other functions and structures, the more detaileddescription of which is not necessary herein. The details of thecellular radio network may deviate from those shown in FIG. 2, but withregard to the invention, these differences have no significance.

[0022] Thus, the cellular radio network typically comprises theinfrastructure of a fixed network, i.e. a network part 200, and userequipment units 202, which can be fixedly positioned, positioned in avehicle, or portable terminals, such as mobile phones or portablecomputers that allow a connection to a radio telecommunications system.The network part 200 comprises base stations 204. The base stationcorresponds to the node B in the preceding figure. A radio networkcontroller 206 connected to the base stations, in turn, controls severalbase stations 204 in a centralized manner. The base station 204comprises transceivers 208 and a multiplexer unit 212.

[0023] The base station 204 further comprises a control unit 210 whichcontrols the operation of the transceiver 208 and the multiplexer 212.By means of the multiplexer 212, the traffic and control channels usedby several transceivers 208 are positioned on one transmission link 214.The transmission link 214 forms the interface Iub.

[0024] There is a connection from the transceiver 208 of the basestation 204 to an antenna unit 218, by means of which a radio connection216 is implemented to the user equipment 202. In the radio connection216, the structure of the frames to be transferred is determined in asystem-specific manner and is called an air interface Uu.

[0025] The radio network controller 206 comprises a group-switchingnetwork 220 and a control unit 222. The group switching network 220 isused for switching speech and data and for connecting signallingcircuits. A radio network subsystem 224 formed by the base station 204and the radio network controller 206 further comprises a transcoder 226.The transcoder 226 is usually positioned as close to the mobile servicesswitching centre 228 as possible, because speech can then be transmittedbetween the transcoder 226 and the radio network controller 206 in theform of a cellular radio network in such a way that transmissioncapacity is saved.

[0026] The transcoder 226 converts the different digital speech codingmodes used between the public switched telephone network and the mobiletelephone network to be compatible with each other, for example from thefixed-network mode into another mode of a cellular radio network, orvice versa. The control unit 222 performs call control, mobilitymanagement, collection of statistical data and signalling.

[0027]FIG. 2 further illustrates a mobile services switching centre 228and a gateway mobile services switching centre 230, which is responsiblefor the connections of the mobile telephone system to the outside world,in this case to a public switched telephone network 232.

[0028]FIG. 3 shows a flow chart of the method steps for attenuatinginterference in a wideband telecommunications system, such as in WCDMAsystems. The method is applicable to removing interference of many typesin wideband systems by adjusting the width of the sample window used inthe method. In one embodiment of the method, interference attenuation isperformed separately for each sample vector, so that the method can alsobe applied to a parallel interference attenuation arrangement.

[0029] Performing the method starts from a block 300. In a block 302, aninterference level threshold is set. The interference level thresholdcan be set in advance, or the interference level threshold can bechanged. Determination of the interference level threshold can be basedon for example measurements performed in the network, advanceinformation on the interfering system or the aim set for the bit errorratio. For instance, if the interfering system is frequency-hopping, theinterference level of the channel can be measured when it is known thatthe interference signal is not on this particular frequency band, andthen the interference level threshold can be set according to themeasurement results received.

[0030] In a block 304, the received signal is sampled by means of amethod according to the prior art. The received signal is composed of adesired signal, noise and interference. The sampling frequency ispreferably one sample per chip, i.e. symbol of a spreading code. If thesampling frequency is something else, the samples can be stored in abuffer memory.

[0031] In a block 306, the baseband sample values are stored as firstsample value vectors of a predetermined length. The length of the samplevalue vectors can be selected freely to be suitable for each system.

[0032] In a block 308, a prediction matrix is formed of each samplevalue vector. In the following, one possible example of forming oneprediction matrix is described when 8 samples have been taken from thereceived signal, in other words when the length of the sample valuevector is 8. The first line in the matrix contains samples 1 to 6 ofeach sample value vector, the next one containing samples 2 to 7 and thethird one containing samples 3 to 8. Thus, the sample vector is slidforwards sample by sample until all elements of one sample vector havebeen positioned in the matrix. After this, the complex conjugate valuesare positioned in the matrix in the reverse order, i.e. at first thecomplex conjugate values of the samples 6 to 1, the complex conjugatevalues of the samples 7 to 2 on the next line, and the complex conjugatevalues of the samples 8 to 3 on the last line. This yields the followingmatrix as the prediction matrix A $\begin{matrix}{A = {\begin{bmatrix}{r(1)} & {r(2)} & {r(3)} & {r(4)} & {r(5)} & {r(6)} \\{r(2)} & {r(3)} & {r(4)} & {r(5)} & {r(6)} & {r(7)} \\{r(3)} & {r(4)} & {r(5)} & {r(6)} & {r(7)} & {r(8)} \\{\overset{\_}{r}(6)} & {\overset{\_}{r}(5)} & {\overset{\_}{r}(4)} & {\overset{\_}{r}(3)} & {\overset{\_}{r}(2)} & {\overset{\_}{r}(1)} \\{\overset{\_}{r}(7)} & {\overset{\_}{r}(6)} & {\overset{\_}{r}(5)} & {\overset{\_}{r}(4)} & {\overset{\_}{r}(3)} & {\overset{\_}{r}(2)} \\{\overset{\_}{r}(8)} & {\overset{\_}{r}(7)} & {\overset{\_}{r}(6)} & {\overset{\_}{r}(5)} & {\overset{\_}{r}(4)} & {\overset{\_}{r}(3)}\end{bmatrix}.}} & (1)\end{matrix}$

[0033] In a block 310, the prediction matrices are modified in such away that the interference components and the desired-signal componentsare separated from each other. This can be implemented by, for example,diagonalization or factorization of the matrix. The diagonalization canbe implemented for instance by means of eigendecomposition, which is,however, applicable to square matrices only. Factorization canpreferably be implemented by means of singular value decomposition(SVD). With singular value decomposition, the data matrix can be dividedinto factors, from which interference compositions and desired-signalcompositions can be separated. SVD is applicable to all kinds ofmatrices, also other than square matrices. By means of singular valuedecomposition, the matrix A can be presented as follows

A=UΣV*  (2)

[0034] where matrices U and V are unitary matrices and Σ is a diagonalmatrix comprising singular matrices of the matrix A. In general, thesingular values are in a descending order. The asterisk denotes acomplex conjugate transpose of the matrix. The 6×6 matrix in theexemplary case yields singular decomposition in which all matrices U, Vand Σ are 6×6 matrices.

[0035] In a block 312, signal matrices are formed by performing rankreduction for each modified prediction matrix by rejecting the samplevalues, the elements representing them or the singular values thatexceed the set interference level threshold. The rank reduction can beperformed by utilizing the Eckhart-Young theorem, which yields the bestleast square estimate of the desired signal.

[0036] In the following, the rank reduction of the matrix is explainedwith reference to the example of FIG. 4. FIG. 4 shows an example of atypical case, where a wideband system is disturbed by a system which isnarrowband in comparison and the power of which is significantly higherthan that of the wideband system. The figure shows samples taken fromthe received signal or elements representing the samples when theinterference components and desired-signal components have beenseparated from each other and shown in the order of magnitude. If thefactorization of the matrix has been performed with singular valuedecomposition, the values in the diagonal form are called singularvalues. The vertical axis indicates the power or amplitude values, thehorizontal axis indicating the samples or elements in the order ofmagnitude. In FIG. 4, the samples, elements or singular values 404, 406,408, 410, 412, 414, 416 comprising only a little or no interference arebelow the set interference level threshold 400; in other words thesesamples, elements or singular values contain only desired signal orwhite gaussian noise. By contrast, a sample, element or singular value402 exceeding the interference level threshold also contains aninterference signal that is at least relatively powerful. Thus, thesample, element or singular value 402 is rejected. In accordance withthe Eckhart-Young theorem, this sample value or element is rejected fromthe matrix Σ, the corresponding columns being rejected from the matricesU and V. A more detailed example of the application of the Eckhart-Youngtheorem is described in publication by Pertti Henttu, Ari Pouttu: ‘BlindSVD Based Interference Suppressor in Spread Spectrum Communications’,which is incorporated as reference herein.

[0037] The prediction matrix of the desired signal according to theEckhart-Young is in the form $\begin{matrix}{\hat{A} = {\sum\limits_{k = 1}^{r_{s}}{\sigma_{k}u_{k}v_{k}^{*}}}} & (3)\end{matrix}$

[0038] where r_(s) is the greatest singular value index, which singularvalue belongs to the estimate of the desired signal.

[0039] In a block 314, new sample value vectors are formed of the signalmatrices by summing up the sample values or elements of the matrix Âwith the corresponding complex conjugates. Thus, in the case of thematrix shown in Formula (1), the sample value estimate {circumflex over(r)}₁ yields the value

{circumflex over (r)}(1)=Â(1,1)+Â(4,6)*  (5)

[0040] and the sample estimate {circumflex over (r)}₂ yields

{circumflex over (r)}(2)=Â(1,2)+Â(2,1)+Â(4,5)*+Â(5,6)*  (6)

[0041] Other sample value estimates are determined correspondingly. Newsample value vectors are formed of the sample value estimates. The abovemethod is preferably repeated for all original sample value vectors.

[0042] In a block 316, sample values of second, i.e. new, sample valuevectors are summed up to average the interference in a time-coherentmanner by sliding the sample value window, the length of which samplevalue window is preferably determined by the length of first, i.e. theoriginal, sample value vectors. The window is slid by one or more samplevalues at a time. The size of the sliding step is determined accordingto each application. In this way, an estimate sampled by means of newsample value vectors can be formed of the received signal, from which atleast samples with strong interference have been filtered out and fromwhich the effect of noise has been averaged out.

[0043]FIG. 5 illustrates an example of noise averaging by sliding thesample value window. FIG. 5 shows, by way of example, only part of thesample value vectors. A sample sequence 500 shows successive samplestaken from the received signal. The samples 500 are preferably stored atfirst in the form of a vector and after that in the form of a matrix forthe purpose of diagonalization and rank reduction. The dimensions of thematrices in the example of FIG. 5 are 8×8. The rank reduction of thematrix is performed in a block 502. After the rank reduction, new samplevalue vectors are formed which comprise samples of a signal with noise.The sample value vectors of FIG. 5 have been formed in accordance withthe method described above. A first element 524 of theinterference-attenuated and noise-attenuated estimate vector of thereceived signal is a sample of a sample vector 504, taken at the momentof time 1. A second element 526 of the interference-attenuated andnoise-attenuated estimate vector of the received signal is the sum ofthe samples of sample vectors 504 and 506, taken at the moment of time2; a third element 528 is the sum of the samples of sample vectors 504,506 and 508, taken at the moment of time 3; and a fourth element 530 isthe sum of the samples of sample vectors 504, 506, 508 and 510, taken atthe moment of time 4. The method is repeated for the next sample block.In FIG. 5, this is illustrated by a ninth element 532 of the estimatevector, which is received by calculating the sum of the samples ofsample vectors 506, 508, 510, . . . , 520, taken at the moment of time9. The sample vectors 504, 506, 508, 510, . . . , 520 can besupplemented with new samples by means of a continuous process, or thesamples can be treated block-specifically.

[0044] The method illustrated by the flow chart of FIG. 3 can beimplemented in a plurality of ways, of which the figure shows twodifferent alternatives. An arrow 318 shows the repeatability of themethod as beginning from the setting of the interference levelthreshold, and an arrow 320 indicates the repeatability of the method asbeginning from the modification of the stored estimate matrices. Theperformance of the method is terminated in a block 322.

[0045] Next, an example of a receiver is described with reference toFIG. 6. FIG. 6 illustrates, for the sake clarity, a simplified exampleof a receiver at a block diagram level by means of one embodiment. Itwill be obvious to a person skilled in the art that a transceiver canalso comprise parts other than the ones shown in FIG. 6. The receivershown can be positioned for instance in the base station of a radiosystem, in a portable communication device, such as a telephone or ahandheld computer or another corresponding device.

[0046] The receiver comprises an antenna or an antenna array 600consisting of antenna elements, and RF (Radio Frequency) parts 602 inwhich the received signal is filtered, down-converted either directly tothe baseband frequency or to intermediate frequency, and amplified.Measurements possibly performed to set the interference level thresholdcan also be performed in the block 602. In a block 604, the signal isconverted from analogue into digital by sampling and quantizing. Anestimate of the received signal according to the above-describedembodiment, from which interference has been attenuated, is formed in ablock 606. In this exemplary case, the block 606 also comprises thememory required for storing the signal sample values. The memory blockcan also be separate. A block 608 comprises a filter matched with theduration of a chip, i.e. a symbol of a spreading code, the filter beingalso used in code search. The filter matched with the chip of the block608 can also be positioned before the block 606. In a block 610, adirect-spread wideband signal is despread by filtering it by means of afilter arranged in the spreading code, which filter is used in signaldetection and synchronization. In a block 612, the signal isdemodulated, and bit decisions are made. The bit decisions can be eitherhard decisions or soft decisions. A block 614 comprises required signalprocessing, such as deinterleaving, decoding and decryption.

[0047] In a preferred embodiment, the receiver, such as a multifingerreceiver of a RAKE type, comprises a delay estimator by means of whichthe delays of the multipath-propagated components are estimated. Thedelays of the different RAKE fingers are set to correspond to the delaysof the signal components delayed in different ways.

[0048] The invention is preferably implemented by software, in whichcase the terminal comprises one or more microprocessors, the functionsaccording to the described interference attenuation method beingimplemented by software operating in the microprocessor(s). Theinvention can also be implemented by hardware solutions providing therequired functionality, for instance by utilizing the ASIC (ApplicationSpecific Integration Circuit) or separate logic components. It is alsoto be noted that the method enables the use of parallel processing.

[0049]FIG. 7 illustrates an example of simulation results of theabove-described interference attenuation method. FIG. 7 shows curves ofthe bit error ratio. The vertical axis shows the number of incorrectbits of all received bits, and the horizontal axis shows the ratio ofthe received bit energy to the noise energy. The simulated system is aDS/FS system, i.e. a direct sequence frequency hopping system. Thelength of the spreading code is 63 chips and the modulation method isBPSK (binary phase shift keying). The length of the frequency hopping is100 bits. The interfering signal is also frequency-hopping, and itsintermediate frequency is converted hop by hop. The interfering signalis a square pulse BPSK signal (SQ BPSK). A curve 700 describesperformance of one of the interference attenuations according to theprior art. The method used is an RLS (Recursive Least Squares) filter. Acurve 702 describes performance of one embodiment of the above-describedinterference attenuation method when the length of the received signalblock is 5 samples; a curve 704 describes performance of one embodimentof the above-described interference attenuation method when the lengthof the received signal block is 8 samples; a curve 706 describesperformance of one embodiment of the above-described interferenceattenuation method when the length of the received signal block is 11samples.

[0050]FIG. 7 shows that the performance of the interference attenuationmethod according to one embodiment of the invention is better than thatof the prior art system, particularly when the signal-noise ratioincreases. The figure also shows that changing the length of thereceived signal block to be processed, and at the same time, changingthe length of the sample window can affect the performance of themethod. The length of the sample block giving the best performancedepends on both the system that is the object of interference and theinterfering system.

[0051] Although the invention is described above with reference to theexample according to the attached drawings, it will be obvious that theinvention is not restricted thereto but can be modified in a pluralityof ways within the inventive idea of the attached claims.

1. A method of attenuating interference in a wideband telecommunicationssystem, characterized by setting an interference level threshold;sampling the received signal; storing the sample values as first samplevalue vectors of a predetermined length, forming prediction matrices ofthe first sample value vectors; modifying prediction matrices in such away that the interference components and the components of the desiredsignal are separated from each other; forming signal matrices byperforming rank reduction for each prediction matrix by rejecting thosesample values or elements representing them that exceed the interferencelevel threshold; forming second sample value vectors of the signalmatrices, the second sample value vectors being at least substantiallyof the same length as the first sample value vectors; summing up samplevalues of second sample value vectors time-coherently to average thenoise by sliding the sample value window, the length of which isdetermined preferably by the length of the first sample value vectors.2. A method according to claim 1, characterized by the interferencelevel threshold being solid.
 3. A method according to claim 1,characterized by the interference level threshold being changeable.
 4. Amethod according to claim 1, characterized by the interference levelthreshold being set on the basis of measurements performed of thechannel.
 5. A method according to claim 1, characterized by the lengthof the sample value vectors being determined by the length of thespreading code.
 6. A method according to claim 1, characterized by theprediction matrices being formed by means of the sample value vectorsand their complex conjugates.
 7. A method according to claim 1,characterized by the rank reduction of the matrix being performed byutilizing the Eckhart-Young theorem.
 8. A method according to claim 1,characterized by the sample value window being slid by one or moresample values at a time.
 9. A method according to claim 1, characterizedby the separation of the interference components and the desired-signalcomponents being performed by diagonalization.
 10. A method according toclaim 1, characterized by the separation of the interference componentsand the desired-signal components being performed by factorization. 11.A receiver in a wideband telecommunications system, in which receiverinterference is attenuated, characterized in that the receiver comprisesmeans (602, 603) for setting an interference level threshold; thereceiver comprises means (604) for sampling the received signal; thereceiver comprises means (606) for storing the sample values as firstsample value vectors of a predetermined length; the receiver comprisesmeans (606) for forming prediction matrices of the first sample valuevectors; the receiver comprises means (606) for modifying predictionmatrices in such a way that the interference components and thecomponents of the desired signal are separated from each other; thereceiver comprises means (606) for forming signal matrices by performingrank reduction for each modified prediction matrix by rejecting thosesample values or elements representing them that exceed the interferencelevel threshold; the receiver comprises means (606) for forming secondsample value vectors of the signal matrices, the second sample valuevectors being at least substantially of the same length as the firstsample value vectors; the receiver comprises means (606) for summing upsample values of second sample value vectors time-coherently to averagethe noise by sliding the sample value window, the length of which isdetermined preferably by the length of the first sample value vectors.12. A receiver according to claim 11, characterized in that theinterference level threshold is fixed.
 13. A receiver according to claim11, characterized in that the interference level threshold ischangeable.
 14. A receiver according to claim 11, characterized in thatthe interference level threshold is set on the basis of the measurementsperformed of the channel.
 15. A receiver according to claim 11,characterized in that the length of the sample value vectors isdetermined by the length of the spreading code.
 16. A receiver accordingto claim 11, characterized in that the prediction matrices are formed bymeans of sample value vectors and their complex conjugates.
 17. Areceiver according to claim 11, characterized in that the rank reductionof the matrix is performed by utilizing the Eckhart-Young theorem.
 18. Areceiver according to claim 11, characterized in that the sample valuewindow is slid by one or more sample values at a time.
 19. A receiveraccording to claim 11, characterized in that the separation of theinterference components and the desired-signal components is performedby diagonalization.
 20. A receiver according to claim 11, characterizedin that the separation of the interfrence components and thedesired-signal components is performed by factorization.